Delay-Minimized Routing in Mobile Cognitive Networks for Time-Critical Applications

Feilong Tang*, Can Tang, Yanqin Yang, Laurence T. Yang, Tong Zhou, Jie Li, Minyi Guo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

Cognitive radio significantly mitigates the spectrum scarcity for various applications built on wireless communication. Current techniques on mobile cognitive ad hoc networks (MCADNs), however, cannot be directly applied to time-critical applications due to channel interference, node mobility as well as unexpected primary user activities. In multichannel multiflow MCADNs, it becomes even worse because multiple links potentially interfere with each other. In this paper, we propose a delay-minimized routing (DMR) protocol for multichannel multiflow MCADNs. First, we formulate the DMR problem with the objective of delay minimization. Next, we propose a delay prediction model based on a conflict probability. Finally, we design the minimized path delay as a routing metric, and propose a heuristic joint routing and channel assignment algorithm to solve the DMR problem. Our DMR can find out the path with a minimal end-to-end (e2e) delay for time-critical data transmission. NS2-based simulation results demonstrate that our DMR protocol significantly outperforms related proposals in terms of average e2e delay, throughput, and packet loss rate.

Original languageEnglish
Article number7569107
Pages (from-to)1398-1409
Number of pages12
JournalIEEE Transactions on Industrial Informatics
Volume13
Issue number3
DOIs
StatePublished - Jun 2017
Externally publishedYes

Keywords

  • Signal collision
  • channel assignment
  • delay prediction
  • mobile cognitive radio network
  • routing

Fingerprint

Dive into the research topics of 'Delay-Minimized Routing in Mobile Cognitive Networks for Time-Critical Applications'. Together they form a unique fingerprint.

Cite this